周期性时间网络上易感-感染-易感动态中的帕隆多悖论。

IF 1.9 4区 数学 Q2 BIOLOGY
Maisha Islam Sejunti , Dane Taylor , Naoki Masuda
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引用次数: 0

摘要

许多社会和生物网络会随着时间的推移而发生周期性的变化,如每天、每周或其他周期。因此,我们提出并分析了周期性时间网络上的易感-传染-易感(SIS)流行病模型。更具体地说,我们假定时间网络由交替使用的静态网络循环组成,每个网络都有给定的持续时间。我们观察到一种现象,即两个静态网络各自都高于流行阈值,但由它们组成的交替网络却使动态低于流行阈值,我们称之为流行病的帕隆多悖论。我们发现,网络结构在形成这一现象中起着重要作用,我们研究了网络结构对网络中子种群之间的连通性和数量的依赖性。我们将这种悖论行为与不同亚群中传染性个体数量的反相振荡动力学联系起来。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Parrondo paradox in susceptible-infectious-susceptible dynamics over periodic temporal networks
Many social and biological networks periodically change over time with daily, weekly, and other cycles. Thus motivated, we formulate and analyze susceptible-infectious-susceptible (SIS) epidemic models over temporal networks with periodic schedules. More specifically, we assume that the temporal network consists of a cycle of alternately used static networks, each with a given duration. We observe a phenomenon in which two static networks are individually above the epidemic threshold but the alternating network composed of them renders the dynamics below the epidemic threshold, which we refer to as a Parrondo paradox for epidemics. We find that network structure plays an important role in shaping this phenomenon, and we study its dependence on the connectivity between and number of subpopulations in the network. We associate such paradoxical behavior with anti-phase oscillatory dynamics of the number of infectious individuals in different subpopulations.
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来源期刊
Mathematical Biosciences
Mathematical Biosciences 生物-生物学
CiteScore
7.50
自引率
2.30%
发文量
67
审稿时长
18 days
期刊介绍: Mathematical Biosciences publishes work providing new concepts or new understanding of biological systems using mathematical models, or methodological articles likely to find application to multiple biological systems. Papers are expected to present a major research finding of broad significance for the biological sciences, or mathematical biology. Mathematical Biosciences welcomes original research articles, letters, reviews and perspectives.
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